Senior AI Product Manager

Sherwin-Williams • Cleveland, OH

4h • $108,531 - $140,086 • Onsite

About The Position

The Senior AI Product Manager leads the development and launch of AI-enabled products from concept through proof of concept, MVP or pilot, scaled deployment, and ongoing improvement, using agile methodologies and product operating model practices. Reporting to the AI Center of Excellence (COE), the role partners closely with the Enterprise Technology Group (ETG) and cross-functional teams to define product requirements and strategy and build, deploy, and enhance AI models, agents, data products, and applications. The role ensures delivery aligns with timelines, budgets, quality standards, Responsible AI requirements, and customer needs, while supporting collaboration, continuous improvement, and innovation.

This position is based at Sherwin-Williams’ Cleveland Headquarters and is not hybrid or remote. It is not eligible for work-authorization sponsorship now or in the future. The role requires 5% travel. As part of its hiring process, the company may review criminal history because the position involves contact with employees and access to confidential or proprietary information and other items of value.

Sherwin-Williams describes its benefits as including a broad range of retirement, health care, well-being, and commute-related offerings. Specific offerings and eligibility are available through the company’s candidate benefits information. Compensation depends on individual and business factors; no wage range is stated in the supplied posting.

Requirements

• Bachelor’s degree in Engineering, Computer Science, Data Science, Statistics, or Business Administration, or at least 7 years of technology product management experience in lieu of a degree.
• At least 4 years of technology product management experience, including launching and managing successful products at scale, and at least 2 years managing production-grade AI/ML, data, or analytics products.
• In-depth knowledge of product development and launch processes, including agile methodologies.
• In-depth knowledge of product innovation methodologies and leading practices.
• Ability to conduct market research and analyze customer needs, market trends, and the competitive landscape.
• Experience developing AI/ML-enabled software products from proof of concept through scaled production deployment.
• Knowledge of UX design principles and customer-centric design thinking.
• Knowledge of business processes, including IT, vendor management, software development lifecycle, and machine-learning (MLOps) lifecycle.
• Excellent communication skills and ability to translate complex technical solutions into business language.
• Working knowledge of predictive modeling, forecasting and optimization, generative AI, large language models, and agentic AI sufficient to guide technical trade-offs with data science and engineering.
• Knowledge of Responsible AI principles, including bias, explainability, privacy, security, and human-in-the-loop design.
• Ability to lead cross-functional pods without direct authority and partner with Enterprise Technology on platform and architecture decisions.
• Experience defining model evaluation, experimentation (such as A/B or test-versus-control), and business-value measurement approaches, including baselines, hypotheses, and pre-agreed success thresholds.
• Understanding of data management and data product principles, including data quality, governance, and semantic layers.
• Must be at least 18 years of age.
• Must be legally authorized to work in the United States without sponsorship now or in the future for employment visa status.
• Technical and skill requirements include agile SDLC and AI/ML MLOps methodologies; agile project management tools; product analytics and BI tools, including SQL; customer relationship management; market research and competitive analysis; product strategy and planning; product risk management; modern delivery; product lifecycle management; demand and capacity management; technology domain knowledge; product optimization and growth strategy; product requirements gathering and documentation; persona creation and journey mapping; reporting tools; AI-assisted development tools; Microsoft 365 and Power Platform; Responsible AI and AI risk management; data and AI platforms; AI/ML model evaluation and experimentation; generative and agentic AI solution design; and data product design and governance.

Nice To Haves

• Agile product management certification, such as PMI-ACP, SAFe POPM, PMC, or CSPO.
• Master’s degree in a quantitative or technical field, or an MBA.
• AI/ML or data platform certification, such as Databricks or Microsoft Azure AI.

Responsibilities

• Develop and execute product strategy, including roadmaps, priorities, release plans, budgets, value cases, positioning, and messaging.
• Define product requirements with business partners and work with cross-functional teams to communicate and execute the product vision.
• Conduct user and market research to identify end-user needs, market trends, competitive threats, and emerging AI/ML capabilities.
• Define, track, and report business value, adoption, and model-performance metrics against baselines and success thresholds established before pilots; recommend whether to ship, iterate, or stop and adjust strategy accordingly.
• Shape and prioritize the product backlog based on business expertise, customer needs, and business value relative to effort, including continuous experimentation after launch.
• Manage AI product development from concept through proof of concept, MVP or pilot, and scaled deployment, ensuring timely, on-budget delivery that meets quality and Responsible AI standards.
• Own and manage product knowledge documentation.
• Communicate product updates and progress to stakeholders and executive leadership, translating technical concepts for non-technical audiences.
• Build and maintain effective working relationships with internal and external stakeholders.
• Analyze product and model performance, user adoption, and customer feedback to identify improvements and drive ongoing product innovation and experimentation.
• Partner with data science and ML engineering to frame business problems as AI/ML use cases; define baselines, hypotheses, model evaluation criteria, acceptance thresholds, experiments, and instrumentation; measure business value; and balance accuracy, explainability, cost, and latency.
• Partner with technology teams to industrialize AI products on enterprise data and AI platforms, including MLOps, monitoring, drift detection, retraining triggers, post-launch evaluation, incident response, inference/token/compute cost management, and transition to run operations.
• Ensure AI products meet AI COE Responsible AI, privacy, security, and governance standards, including risk tiering, evaluation and red-teaming before scale, human-in-the-loop design, risk mitigation, and go/no-go recommendations with Legal, Privacy, and Cybersecurity.
• Define and enforce data requirements, including data quality, lineage, and semantic-layer standards for AI models, agents, and data products.
• Define agentic AI product requirements, including autonomy levels, tool use, guardrails, and agent-specific evaluation.
• Drive end-user adoption and change management with business leaders, including training, process redesign, and feedback loops.

Benefits

• A broad range of benefits, including retirement, health care, well-being, and commute-related offerings; specific benefits and eligibility are available through the company’s candidate benefits information.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior